A ResNet-101 [1]} backbone is used to extract image features \(\mathbf {\tilde{F}} \in \mathbb {R}^{W_F \times H_F \times C}\)  (see Image Backbone in Figure REF ). In our implementation, we extract the image features from Block1 of the ResNet-101 backbone in order to maintain a high spatial resolution. A high spatial resolution is necessary for an effective frustum to voxel grid transformation, such that the frustum grid can be finely sampled without repeated features.
